Donald Martorello and Allison Mains
Many predator species select their prey based on the prey densities. Ecologists have observed predator selection in many systems including both aquatic and terrestrial. Predators often develop a search image based on the prey form that they encounter most frequently. The predator may forage exclusively on that prey type until a different prey is encountered more frequently or until forage rates are too low to maintain the predator's energy requirements. In addition, a predator's search efficiency (search distance and search speed) may also affect prey selection. This concept is generally known as prey switching. For example, an avian predator, lets say a Red-tailed hawk, may select the rodent species it sees most frequently as its prey. The hawk may continue to prey on that species until it can't find anymore or until some other rodent species is even more abundant. When the hawk changes from foraging on one species to another, prey switching has occurred. In this lab, we will simulate a system that depicts prey switching. The lab will investigate the relationship between prey switching and prey population sizes, predator search distance, predator search speed, and forage rates
Outline of this Lab
1. Run EcoBeaker (double-click on its icon)
2. Open the situation "Prey Switching" (use the open command in the file menu).You should see four windows laid out on the screen as follows:
3. Start the simulation by clicking the "Go" button.You will see three habitat types with a predator species (Red-tailed hawk) and two prey species (vole and mouse). The Red-tailed hawk is the red dot, the voles are the light green dots, and the mice are the light blue dots. The Red-tailed hawk is able to forage on either species, however the voles forage only on tall grass (dark green habitat) and the mice forage only on shrubs (dark blue habitat).At the start of the simulation, 1 hawk, 5 voles, and 5 mice are present. The simulation is limited to 1 hawk throughout, but prey abundance may increase with forage availability or decrease because of predation. The simulation starts with the Red-tailed hawk preying on voles or mice. Once the hawk consumes a prey, a search image is formed and the hawk continues to prey only on that prey species. If the hawk does not consume a prey item within 60 time steps, the search image is abandoned and the hawk again preys indiscriminately; the hawk will re-establish a search image on the next prey encountered. Notice the bar chart window. Each time the hawk switches prey species the bar moves from one side to the other. Also, notice the chart displaying the population size of the prey species and the corresponding fluctuations as the hawk switches from one prey to the other.
4. Stop the simulation from running (push the STOP button on the control panel).The simulation assumes that the prey species seen are not the only individuals present. The voles and mice seen are individuals that are at risk to predation (i.e., above the threshold of security). Other voles and mice that are not at risk to predation (i.e., below the threshold of security) are assumed to be present but are not seen.Now we're ready to vary the prey numbers and observe the effect it has on prey switching.
5. Restart the simulation by re-opening the file. Now increase the density of voles by increasing the immigration parameter from 0.1 to 0.5 and press "Go."Do you notice any differences in the frequency of prey switching? How does the maximum number of voles and mice compare to the previous situation? By changing of the immigration parameter find the highest value that still results in prey switching. Now repeat the same simulation for the mouse prey. Do you obtain the same maximum immigration value that still results in prey switching? If the values differ, what might be the cause?
Notice that while the hawk preys on one species, the other prey species increases toward carrying capacity as defined by food availability. Remember that if the hawk reduces a prey population to zero, prey below the threshold of security are present but are not seen.
6. Stop the simulation from running (push the STOP button on the control panel).Now lets change how long the hawk will go without food until it switches.
7. Restart the simulation by re-opening the file again. Now decrease the time until switch from 60 to 20 and press "Go."What are your observations? Try adjusting the prey immigration rates to so the hawk will forage on the prey with the highest density (hint: reduce prey immigration).Do you notice any trends? Write down your observations.
8. Now let's make a more efficient predator. Re-open the file and change the search distance parameter to 20 and press "Go."What happens to the frequency of switching? Do you think changing the speed of the predator will have a similar effect? Test you hypothesis.What can you conclude about the factors that affect switching?
(Optional)9. If there is time, increase the number of hawks present to 2 and run the simulation. You can accomplish this by increasing the hawk immigration above zero for only a few time steps. Once you see a second hawk appear, change the immigration value back to zero. What observations can you make? Is this a realistic result? If not, what other factors might affect prey switching?
Notes and Comments
As you have observed in this lab, there are many factors that affect the dynamics of prey switching. We have only explored a few of these factors. As the complexity of a system increases, correctly identifying those factors that drive switching becomes more difficult. Imagine the difficulty an ecologist has when managing species that are influenced by switching. Understanding the basic forces driving switching will help in the understanding of community interactions.
Kotler, B. P. 1984. Risk of predation and the structure of desert rodent communities. Ecology 65:689-701.Murdoch, W. W. and J. R. Marks. 1981. Predation by Coccinellid beetles: experiments on switching. Ecology 54:160-167.
Stamps, J., S. Tanaka, and V. V. Krishnan. 1981. The relationship between selectivity and food abundance in juvenile lizards. Ecology 62:1079-1092.